Ultrasound imaging is a medical imaging technique for imaging organs and soft tissues in a human body. Ultrasound imaging uses real time, non-invasive high frequency sound waves to produce two-dimensional (2D) and/or three-dimensional (3D) images.
In some instances, ultrasonic scanners may utilize frame rate upconversion. In this regard, frame rate upconversion may be used when performing ultrasound scans of particular organs (e.g., cardiac scans) where the scan frame rate may be lower than necessary (e.g., too slow to show particular elements and/or features, such as valve movement in the heart). Use of frame rate upconversion, however, may address some of these issues. In particular, frame rate upconversion may make ultrasonic images smoother, and as such it may potentially increase the diagnostic value of the ultrasonic scan.
Various methods may be used to provide frame rate upconversion. For example, frame rate upconversion may be achieved by interpolating frames from existing frames. In this regard, linear interpolation is one way of increasing frame rate. However, ghosting and blurring are the main drawbacks of this type of interpolation. Thus, various techniques may be used in conjunction with frame interpretation to address some of the drawbacks.
For example, motion estimation and motion compensation techniques may be used to address such defects as blurring and ghosting. Nonetheless, motion estimation and motion compensation techniques that are typically used in optical imaging are not suitable for low frame rate cardiac ultrasound imaging, because of speckle noise as well as large movement of the cardiac valves compared to other anatomical features. In this regard, prior art in motion compensated framerate upconversion in optical images, typically focus on the motion estimation.
The most basic way to find the velocity vector is to use regular forward or backward block-matching. This procedure has some flaws, however. For example, as a pixel in the frame to be interpolated may have many or none velocity vectors passing through it, and as such the interpolated frame may contain holes or overlapping pixels. One way to work around the effect of holes and overlaps is to utilize bidirectional motion estimation (BME). In bidirectional motion estimation a regular forward block matching may be performed first, and the result of that matching may then be used as a starting point for a new and limited search starting from a point in the frame to be interpolated. The result is later smoothed and overlap is used to improve robustness. Bidirectional tracking can find erroneous temporal symmetries. Dual motion estimation tries to overcome this problem by adding a reliability test criterion on the bidirectional tracking results. Vectors may be calculated using overlap and if the result is deemed unreliable, neighboring results are weighted in. This method is limited, however, by the quality of the reliability test criterion. One criterion can be the discrepancy between estimated forward and backward velocity vectors.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.